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sidebar_label: "Nvidia GPU"
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# Nvidia GPU


<img src="https://netdata.cloud/img/nvidia.svg" width="150"/>


Plugin: go.d.plugin
Module: nvidia_smi

<img src="https://img.shields.io/badge/maintained%20by-Netdata-%2300ab44" />

## Overview

This collector monitors GPUs performance metrics using
the [nvidia-smi](https://developer.nvidia.com/nvidia-system-management-interface) CLI tool.




This collector is supported on all platforms.

This collector supports collecting metrics from multiple instances of this integration, including remote instances.


### Default Behavior

#### Auto-Detection

This integration doesn't support auto-detection.

#### Limits

The default configuration for this integration does not impose any limits on data collection.

#### Performance Impact

The default configuration for this integration is not expected to impose a significant performance impact on the system.

## Metrics

Metrics grouped by *scope*.

The scope defines the instance that the metric belongs to. An instance is uniquely identified by a set of labels.



### Per gpu

These metrics refer to the GPU.

Labels:

| Label      | Description     |
|:-----------|:----------------|
| uuid | GPU uuid (e.g. GPU-27b94a00-ed54-5c24-b1fd-1054085de32a) |
| index | GPU index (nvidia_smi typically orders GPUs by PCI bus ID) |
| product_name | GPU product name (e.g. NVIDIA A100-SXM4-40GB) |

Metrics:

| Metric | Dimensions | Unit |
|:------|:----------|:----|
| nvidia_smi.gpu_pcie_bandwidth_usage | rx, tx | B/s |
| nvidia_smi.gpu_pcie_bandwidth_utilization | rx, tx | % |
| nvidia_smi.gpu_fan_speed_perc | fan_speed | % |
| nvidia_smi.gpu_utilization | gpu | % |
| nvidia_smi.gpu_memory_utilization | memory | % |
| nvidia_smi.gpu_decoder_utilization | decoder | % |
| nvidia_smi.gpu_encoder_utilization | encoder | % |
| nvidia_smi.gpu_frame_buffer_memory_usage | free, used, reserved | B |
| nvidia_smi.gpu_bar1_memory_usage | free, used | B |
| nvidia_smi.gpu_temperature | temperature | Celsius |
| nvidia_smi.gpu_voltage | voltage | V |
| nvidia_smi.gpu_clock_freq | graphics, video, sm, mem | MHz |
| nvidia_smi.gpu_power_draw | power_draw | Watts |
| nvidia_smi.gpu_performance_state | P0-P15 | state |
| nvidia_smi.gpu_mig_mode_current_status | enabled, disabled | status |
| nvidia_smi.gpu_mig_devices_count | mig | devices |

### Per mig

These metrics refer to the Multi-Instance GPU (MIG).

Labels:

| Label      | Description     |
|:-----------|:----------------|
| uuid | GPU uuid (e.g. GPU-27b94a00-ed54-5c24-b1fd-1054085de32a) |
| product_name | GPU product name (e.g. NVIDIA A100-SXM4-40GB) |
| gpu_instance_id | GPU instance id (e.g. 1) |

Metrics:

| Metric | Dimensions | Unit |
|:------|:----------|:----|
| nvidia_smi.gpu_mig_frame_buffer_memory_usage | free, used, reserved | B |
| nvidia_smi.gpu_mig_bar1_memory_usage | free, used | B |



## Alerts

There are no alerts configured by default for this integration.


## Setup


You can configure the **nvidia_smi** collector in two ways:

| Method                | Best for                                                                                 | How to                                                                                                                                 |
|-----------------------|------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------|
| [**UI**](#via-ui)     | Fast setup without editing files                                                         | Go to **Nodes → Configure this node → Collectors → Jobs**, search for **nvidia_smi**, then click **+** to add a job. |
| [**File**](#via-file) | If you prefer configuring via file, or need to automate deployments (e.g., with Ansible) | Edit `go.d/nvidia_smi.conf` and add a job.                                                                        |

:::important

UI configuration requires paid Netdata Cloud plan.

:::


### Prerequisites

No action required.

### Configuration

#### Options

The following options can be defined globally: update_every, autodetection_retry.


<details open><summary>Config options</summary>



| Option | Description | Default | Required |
|:-----|:------------|:--------|:---------:|
| update_every | Data collection frequency. | 10 | no |
| autodetection_retry | Autodetection retry interval (seconds). Set 0 to disable. | 0 | no |
| binary_path | Path to nvidia_smi binary. The default is "nvidia_smi" and the executable is looked for in the directories specified in the PATH environment variable. | nvidia_smi | no |
| timeout | The maximum duration, in seconds, to wait for an `nvidia-smi` command to complete. This setting applies differently based on the collector's mode. **Loop Mode:** In loop mode, the timeout primarily determines how long to wait for the initial `nvidia-smi` execution. If the initial query takes longer than the timeout, the collector may report an error. For systems with multiple GPUs, the initial load time can sometimes be significant (e.g., 5-10 seconds). **Regular Mode:** If the collector is in regular mode, the timeout specifies how long to wait for each individual `nvidia-smi` execution. | 10 | no |
| loop_mode | When enabled, `nvidia-smi` is executed continuously in a separate thread using the `-l` option. | yes | no |


</details>


#### via UI

Configure the **nvidia_smi** collector from the Netdata web interface:

1. Go to **Nodes**.
2. Select the node **where you want the nvidia_smi data-collection job to run** and click the :gear: (**Configure this node**). That node will run the data collection.
3. The **Collectors → Jobs** view opens by default.
4. In the Search box, type _nvidia_smi_ (or scroll the list) to locate the **nvidia_smi** collector.
5. Click the **+** next to the **nvidia_smi** collector to add a new job.
6. Fill in the job fields, then click **Test** to verify the configuration and **Submit** to save.
    - **Test** runs the job with the provided settings and shows whether data can be collected.
    - If it fails, an error message appears with details (for example, connection refused, timeout, or command execution errors), so you can adjust and retest.


#### via File

The configuration file name for this integration is `go.d/nvidia_smi.conf`.

The file format is YAML. Generally, the structure is:

```yaml
update_every: 1
autodetection_retry: 0
jobs:
  - name: some_name1
  - name: some_name2
```
You can edit the configuration file using the [`edit-config`](https://github.com/netdata/netdata/blob/master/docs/netdata-agent/configuration/README.md#edit-a-configuration-file-using-edit-config) script from the
Netdata [config directory](https://github.com/netdata/netdata/blob/master/docs/netdata-agent/configuration/README.md#the-netdata-config-directory).

```bash
cd /etc/netdata 2>/dev/null || cd /opt/netdata/etc/netdata
sudo ./edit-config go.d/nvidia_smi.conf
```

##### Examples

###### Custom binary path

The executable is not in the directories specified in the PATH environment variable.

<details open><summary>Config</summary>

```yaml
jobs:
  - name: nvidia_smi
    binary_path: /usr/local/sbin/nvidia_smi

```
</details>



## Troubleshooting

### Debug Mode

**Important**: Debug mode is not supported for data collection jobs created via the UI using the Dyncfg feature.

To troubleshoot issues with the `nvidia_smi` collector, run the `go.d.plugin` with the debug option enabled. The output
should give you clues as to why the collector isn't working.

- Navigate to the `plugins.d` directory, usually at `/usr/libexec/netdata/plugins.d/`. If that's not the case on
  your system, open `netdata.conf` and look for the `plugins` setting under `[directories]`.

  ```bash
  cd /usr/libexec/netdata/plugins.d/
  ```

- Switch to the `netdata` user.

  ```bash
  sudo -u netdata -s
  ```

- Run the `go.d.plugin` to debug the collector:

  ```bash
  ./go.d.plugin -d -m nvidia_smi
  ```

  To debug a specific job:

  ```bash
  ./go.d.plugin -d -m nvidia_smi -j jobName
  ```

### Getting Logs

If you're encountering problems with the `nvidia_smi` collector, follow these steps to retrieve logs and identify potential issues:

- **Run the command** specific to your system (systemd, non-systemd, or Docker container).
- **Examine the output** for any warnings or error messages that might indicate issues.  These messages should provide clues about the root cause of the problem.

#### System with systemd

Use the following command to view logs generated since the last Netdata service restart:

```bash
journalctl _SYSTEMD_INVOCATION_ID="$(systemctl show --value --property=InvocationID netdata)" --namespace=netdata --grep nvidia_smi
```

#### System without systemd

Locate the collector log file, typically at `/var/log/netdata/collector.log`, and use `grep` to filter for collector's name:

```bash
grep nvidia_smi /var/log/netdata/collector.log
```

**Note**: This method shows logs from all restarts. Focus on the **latest entries** for troubleshooting current issues.

#### Docker Container

If your Netdata runs in a Docker container named "netdata" (replace if different), use this command:

```bash
docker logs netdata 2>&1 | grep nvidia_smi
```


